This work reports development of a two-stage methodology for multiobjective batch plant design, which may be viewed as an alternative to traditional approaches based on mathematical programming techniques: (1) At the upper level, a genetic algorithm (GA) has been developed for solving the problem of design and proposing several plant structures. This kind of algorithm has proven previously its efficiency for the treatment of combinatorial problems. (2) At the inner level, a discrete-event simulation model (DES) tests the technical feasibility of the generated configurations. Part 1 of this series of papers is devoted to the implementation of the DES model whereas part 2 will tackle the development of the GA. The basic principles of the development of the design-oriented DES model are first recalled, and then the various potential uses of the simulator are presented. A detailed account of model assumptions for design purpose is also given. The formalism is illustrated by a typical example serving as a test bench in part 2.